Noticeability Versus Impact in Traffic Signal Tampering

Bilal Thonnam Thodi, Timothy Mulumba, Saif Eddin Jabari

Research output: Contribution to journalArticlepeer-review


This paper investigates the vulnerability of urban traffic networks to cyber attacks on traffic lights. We model traffic signal tampering as a bi-objective optimization problem that simultaneously seeks to reduce vehicular throughput in the network over time (maximize impact) while introducing minimal changes to network signal timings (minimize noticeability). We represent the Spatio-temporal traffic dynamics as a static network flow problem on a time-expanded graph. This allows us to reduce the (non-convex) attack problem to a tractable form, which can be solved using traditional techniques used to solve linear network programming problems. We show that minor but objective adjustments in the signal timings over time can severely impact traffic conditions at the network level. We investigate network vulnerability by examining the concavity of the Pareto-optimal frontier obtained by solving the bi-objective attack problem. Numerical experiments are carried to illustrate the types of insights that can be extracted from the Pareto-optimal frontier. For instance, our experiments suggest that the vulnerability of a traffic network to signal tampering is independent of the demand levels.

Original languageEnglish (US)
Article number9086475
Pages (from-to)86149-86161
Number of pages13
JournalIEEE Access
StatePublished - 2020


  • Network vulnerability
  • adversarial attacks
  • cybersecurity
  • signal tampering
  • traffic flow dynamics
  • urban traffic networks

ASJC Scopus subject areas

  • General Computer Science
  • General Materials Science
  • General Engineering


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